Publications

A signal pre-compensation system analyzes one or more properties of a communication medium and, taking advantage of the locality of…

We present streaming CP update, an algorithmic framework for updating CP tensor decompositions that possesses the capability of identifying emerging…

Multiresolution priority queues are data structures recently discovered by Reservoir Labs that reduce the entropy of some critical graph algorithms—such…

As the scale of unlabeled data rises, it becomes increasingly valuable to perform scalable, unsupervised data analysis. Tensor decompositions, which…

In this paper we introduce a new framework to detect elephant flows at very high speed rates and under uncertainty.…

Heavy-hitter flows or Cheetah Flows (CF), which are high-rate flows can result in increased packet losses and delay in general…

Tensor decompositions are a class of algorithms used for unsupervised pattern discovery. Structured, multidimensional datasets are encoded as tensors and…

As the sheer amount of computer generated data continues to grow exponentially, new bottlenecks are unveiled that require rethinking our…

Methods, apparatus and computer software product for optimization of data transfer between two memories includes determining access to master data…